Field-calibrated hydraulic feedback for optimizing rotational irrigation grouping in cotton drip-irrigation networks

Rotational irrigation grouping changes network flow paths and distal pressures; empirical grouping or nominal-flow balancing therefore may not ensure hydraulic feasibility. For an automated cotton drip-irrigation system in Xinjiang, China, we coupled a field-calibrated EPANET model with CP-SAT in a closed loop. Type-specific minimum operating pressure heads for short- and long-hose units were derived from field pressure–discharge responses. CP-SAT generated candidate groups subject to fixed group size, outlet-hydrant mutual exclusion, branch-load balancing, and high-risk-unit dispersion. EPANET checked each group, and every complete infeasible nine-unit combination was returned as a no-good constraint before re-optimization. After calibration, model MAE, RMSE, and $$R^2$$ were 0.264 m, 0.346 m, and 0.842; matched-condition holdout validation yielded 0.391 m, 0.488 m, and 0.727, respectively. The adopted pressure heads were 4.6 m for short-hose units and 4.9 m for long-hose units. All 19 final groups met the adopted type-specific pressure criteria in steady-state hydraulic simulations, while the field-tested groups achieved a pressure-satisfaction rate of 97.22%. The dripper-discharge coefficient of variation, Christiansen uniformity coefficient, and low-quarter distribution uniformity in the field-tested groups were 8.06%, 93.02%, and 89.58%, respectively. Under the observed operating conditions, feedback removed low-pressure combinations missed by nominal load balancing.